CONTENTS: 1. Foundations of Artificial Intelligence and Machine Learning 2. Machine Learning Algorithms and Techniques 3. AI Applications in Real World Scenarios 4. Ethical Considerations and Challenges 5. The Future of AI and ML 6. Deep Learning and Neural Networks 7. Reinforcement Learning and Robotics 8. Time Series Analysis and Forecasting 9. Explainability and Interpretability in AI 10. AI and ML